Extracting a neural connectome from an EM dataset is complex and timing consuming. Scalable, high-quality image technology and advanced segmentation algorithms are critical components to these efforts and are justifiably highlighted in journals and conferences. However, converting a segmented dataset into a validated connectivity graph is an understated and perhaps even harder task. The myriad of tools, processes, and management necessary to produce a connectome do not always neatly fit into a traditional journal article. This blog aims to discuss all aspects of the connectome reconstruction pipeline.
Recipe for a Connectome
April 23, 2020
After successfully producing the largest dense connectome in the world, do we now possess a recipe for efficiently mapping even larger nervous systems? Read more »
Data Management in Connectomics
October 18, 2019
Data engineering can be an unglamorous aspect of connectomics compared to 3D visualization and deep learning. Yet the choices we make in how to store and access data impact every part of our reconstruction pipeline, including how we distribute the data and collaboratively edit it. Read more »
Building the Team to Build the Connectome
August 27, 2019
Producing large connectomes require a tremendous amount of diverse talent working in harmony. Organizing the team for maximum effectiveness and efficiency is critically important to success. Read more »
July 30, 2019
Comparative connectomics is a simple and appealing idea. Examine the brain of an animal that has learned a task, or has a genetic variant, and compare it to the brain of a control animal. This seems particularly appealing in the brain of the fruit fly, where the organization and circuits of the brain are very similar from animal to animal. But this is a lot harder than it first appears. Read more »
Sparse is Not Enough
July 10, 2019
Before recent advances in automated segmentation, comprehensively or densely reconstructing all neurons and (most) connections in a dataset was infeasible except for relative small datasets. Instead, biologists sparsely traced the neurons most relevant to their work. But sparse is not enough. Read more »
My EM Data is Segmented. Now What?
June 17, 2019
You toil for years perfecting brain sample preparation and imaging techniques. Applying the latest deep learning techniques to your data produces amazing automated neuron segmentation, sometimes to near perfection [see figure]. Now real neuroscience can begin … well not necessarily. Read more »
We are the members of the FlyEM project team and are on a quest to reconstruct ground-breaking neural connectomes in the fly nervous system. The goals of this blog are to highlight some of our challenges and solutions in producing large connectomes.
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Manager of FlyEM & Connectome Research Team Leader